Data-centric to data-driven: the real transformation behind industry 4.0
How to change the way data is managed in the organisation, scale-up digitisation and become a data-driven industry.
How to change the way data is managed in the organisation, scale-up digitisation and become a data-driven industry.
Contextualising data is a hot topic in the industrial sector. Although it’s not a new concept, it’s gaining attention as industries face growing challenges that can only be solved through contextualisation.
Real-time control and optimization of batch industrial processes: an innovative approach leveraging advances in online analysis, digitalization, and AI.
Industrial companies still fail to make widespread use of data in their plant. It is 2022 and this statement is still true. Why industrial companies are failing? Main obstacles and key drivers to scale-up data use in the plant…
The year 2022 is marked by tensions on energy supply. At the same time, new measures are being implemented to force players to reduce their CO2 emissions. Some of the causes of these tensions may be temporary, but most are structural and will persist…
Data and digitization are transforming deeply how operational teams are working, and we must say, it is a great opportunity for them as well as for their organisation.
Productivity is a key challenge for industrials. Producing more from existing assets has several positive impacts on profitability. But how can it be improved?
Through the implementation of OIAnalytics on Adisseo’s sites, discover the key success factors of a successful group-wide digital transformation.
How can a global approach to data improve your performance in the long term? Move from data to action and improve your performance.
Discover the objectives of identifying the factors influencing a production process, our approach and the approach we recommend.
Enterprise Manufacturing Intelligence: solutions to enhance the value of information, focused on the uses and autonomy of users around data.
Now implemented on the toner production line, the OIAnalytics solution provides TOSHIBA Dieppe’s teams with a collaborative tool to improve productivity and industrial performance.
Facilitating interactions between teams: how does digitalization make it possible to dematerialize support for industrial performance?
Contributions of Data Science and Machine Learning in the field. Discover the many opportunities to gain performance in the plant by overcoming the limitations of these approaches.
Quickly and autonomously set up the collection of data from industrial pilots and simplify their processing : Eramet testimony.
